Failure prediction on railway turnouts using time delay neural networks

Turnout systems on railways play critical role on reliability of railway infrastructure. Identification and prediction of failures on mechanical systems have been attracting researchers and industry in recent years. Condition based maintenance focuses on failure identification and prediction using sensory information collected real-time from sensors embedded on electro-mechanical systems. This paper presents neural network based failure prediction algorithm on railway turnouts.